Many diseases present with specific structural phenotypes, as with the distinct facial features of patients with Cornelia de Lange Syndrome. Similarly, specific structural signatures for many diseases are accessible via cellular images. As such, automated microscopic imaging provides a suitable basis for a high throughput screening platform to study these specific cellular structural signatures. Microscopic imaging provides information on functional data points together with associated spatial information in x, y and z dimensions.
Microscopic imaging techniques have advanced over the past few years. Advances in optics, robotics and computational techniques, as well as an expanding repertoire of contrast markers, including functional live-cell reporters, are contributing to the widespread adoption of image-based screening platforms that provide highly dynamic and quantitative fluorescence readouts in cell-based assay systems. See Bickle, 2010, “The beautiful cell: high-content screening in drug discovery,” Anal. Bioanal Chem. 398, 219-226; Isherwood et al., 2011, “Live cell in vitro and in vivo imaging applications: accelerating drug discovery,” Pharmaceutics 3, 141-170 (2011); and Kummel et al., 2010, “Integration of multiple readouts into the z′ factor for assay quality assessment,” J. Biomol. Screen 15, 95-101.
Non-invasive, label-free imaging techniques have recently emerged, fulfilling the requirements of minimal cell manipulation for cell-based assays in a high-content screening context. Among these label-free techniques, digital holographic microscopy (Rappaz et al., 2015 Automated multi-parameter measurement of cardiomyocytes dynamics with digital holographic microscopy,” Opt. Express 23, 13333-13347) provides quantitative information that is automated for end-point and time-lapse imaging using 96- and 384-well plates. See, for example, Kuhn, J. 2013, et al., “Label-free cytotoxicity screening assay by digital holographic microscopy,” Assay Drug Dev. Technol. 11, 101-107; Rappaz et al., 2014 “Digital holographic microscopy: a quantitative label-free microscopy technique for phenotypic screening,” Comb. Chem. High Throughput Screen 17, 80-88; and Rappaz et al., 2015 in Label-Free Biosensor Methods in Drug Discovery (ed. Fang, Y.) 307-325, Springer Science+Business Media). Similarly, label-free optical techniques such as phase contrast or differential interference contrast (DIC) can be digitally reconstructed and quantified. See Koos, 2015, “DIC image reconstruction using an energy minimization framework to visualize optical path length distribution,” Sci. Rep. 6, 30420. Light sheet fluorescence microscopy (LSFM) holds promise for the analysis of large numbers of samples, in 3D high resolution and with fast recording speed and minimal photo-induced cell damage. LSFM has gained increasing popularity in various research areas, including neuroscience, plant and developmental biology, toxicology and drug discovery, although it is not yet adapted to an automated HTS setting. See, Pampaloni et al., 2014, “Tissue-culture light sheet fluorescence microscopy (TC-LSFM) allows long-term imaging of three-dimensional cell cultures under controlled conditions,” Integr. Biol. (Camb.) 6, 988-998; Swoger et al., 2014, “Imaging cellular spheroids with a single (selective) plane illumination microscope,” Cold Spring Harb. Protoc., 106-113; and Pampaloni et al., 2013, “High-resolution deep imaging of live cellular spheroids with light-sheet-based fluorescence microscopy,” Cell Tissue Res. 352, 161-177.
Cell Painting and related variants of cell painting represent another form of imaging technique that holds promise. Cell painting is a morphological profiling assay that multiplexes six fluorescent dyes, imaged in five channels, to reveal eight broadly relevant cellular components or organelles. Cells are plated in multiwell plates, perturbed with the treatments to be tested, stained, fixed, and imaged on a high-throughput microscope. Next, automated image analysis software identifies individual cells and measures any number between one and tens of thousands (but most often approximately 1,000) morphological features (various measures of size, shape, texture, intensity, etc. of various whole-cell and sub-cellular components) to produce a profile that is suitable for the detection of even subtle phenotypes. Profiles of cell populations treated with different experimental perturbations can be compared to suit many goals, such as identifying the phenotypic impact of chemical or genetic perturbations, grouping compounds and/or genes into functional pathways, and identifying signatures of disease. See, Bray et al., 2016, Nature Protocols 11, 1757-1774.
Microscopic imaging allows for high throughput screening in which cells are perturbed with a perturbation, such as an siRNA that is designed to disrupt a single gene within the cell while minimizing disruption of other genes, and the microscopic imaging is used to quantify the effects of such perturbations. In fact, such screening can be used to first identify a perturbation that causes cells to have the characteristics of a disease of interest, and further used to determine which compounds rescue the disease-associated characteristics induced by virtue of the perturbation. A drawback of known imaging techniques for such high throughput screening efforts is that they are expensive, inefficient and/or lack sufficient throughput potential.
A drawback that arises in known screening techniques, including cell painting, is that the magnitude and prevalence of off target effects cause the morphological profiles of perturbations targeting the same gene to look more dissimilar than those targeting different genes. See Singh et al., 2015, “Morphological profiles of RNAi-induced gene knockdown are highly reproducible but dominated by seed effects,” PLoS One 10, e0131370. This phenomenon has been observed in other multiparametric assays, and it is not specific to morphological profiling using imaging techniques. This effect impedes large-scale experiments using perturbations such as short RNAi reagents, or any other perturbation with significant off target effects, in which the experimental design requires widespread comparisons across all samples.
Given the above background, what is needed in the art are systems and methods for compensating for off target effects in order to identify a set of perturbations that have an on target effect against a selected target.